Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

As of August 17, 2023, data is being updated each Friday.

For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

This infographic demonstrates the journey of data and how respondents' answers to our surveys become useful data used to make informed decisions. The infographic highlights the Labour Force Survey (LFS), the Survey of Household Spending (SHS), and the Canadian Community Health Survey (CCHS).

This table contains 2 series, with data for years 1852 - 1977 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (1 items: Canada ...) Estimates (2 items: Estimated population; Immigrant arrivals ...).

Labour statistics by job category, for Canada, the provinces and territories, annual.

Get statistical data on greenhouse industry statistics for Ontario and Canada.

This dataset includes:

• square footage
• sales
• employee numbers
• selected input costs

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

This table contains 10 series, with data for years 1981 - 1985 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Estimates (2 items: Tonnes; Dollars); Standard Classification of Goods (SCG) (5 items: Chocolate confectionery; Sugar confectionery; Chewing gum; Popcorn; ...).

Sheep statistics, supply and disposition of sheep and lambs, Canada and provinces (head x 1,000). Data are available on an annual basis.

This table contains 22 series, with data for years 1871 - 1971 (not all combinations necessarily have data for all years), and was last released on 2012-02-16. This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (1 items: Canada ...) Birthplace (4 items: Total; all birthplaces; Canadian-born; Foreign-born; Other British-born ...) Type of area (3 items: Total urban and rural; Rural; Urban ...) Sex (3 items: Both sexes; Males; Females ...).

Statistical data tables presented in the CBSA’s annual report on requests made under the Access to Information Act. NOTE: All CBSA Access to Information statistics are now published under TBS Access to Information and Privacy Statistics: https://open.canada.ca/data/en/dataset/236294e1-bc74-486f-ab97-422227bc8832

An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protection's CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990+. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system. This service depicts the WHRTYPE description from the fveg dataset (Wildlife Habitat Relationship classes).The full dataset can be downloaded in raster format here: GIS Mapping and Data Analytics | CAL FIREThe service represents the latest release of the data, and is updated when a new version is released. Currently it represents fveg15_1.

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of consumer goods and general rental (NAICS 5322 & 5323), annual, for five years of data.

Canada CA: School Enrollment: Preprimary: % Gross data was reported at 48.920 % in 2020. This records an increase from the previous number of 48.765 % for 2018. Canada CA: School Enrollment: Preprimary: % Gross data is updated yearly, averaging 56.053 % from Dec 1971 (Median) to 2020, with 28 observations. The data reached an all-time high of 64.441 % in 1996 and a record low of 40.556 % in 1971. Canada CA: School Enrollment: Preprimary: % Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Social: Education Statistics. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed October 24, 2022. https://apiportal.uis.unesco.org/bdds.;Weighted average;

The Ontario Economic Accounts (OEA) is a public document, released four times a year that provides an overall assessment of the current state of the Ontario economy. OEA estimates are based on Statistics Canada data. Its primary audience includes economists in both public and private sectors and credit rating agencies.

*[OEA]: Ontario Economic Accounts

Number of persons in low income, low income rate and average gap ratio by economic family type, annual.

Categorized library statistical reports for the population group of 100,001 to 250,000.

About this dataset

Context

The dataset tabulates the population of Oakland by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Oakland. The dataset can be utilized to understand the population distribution of Oakland by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Oakland. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Oakland.

Key observations

Largest age group (population): Male # 30-34 years (22,845) | Female # 30-34 years (23,128). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Oakland population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Oakland is shown in the following column.
• Population (Female): The female population in the Oakland is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Oakland for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Oakland Population by Gender. You can refer the same here

The summary statistics by North American Industry Classification System (NAICS) which include: operating revenue (dollars x 1,000,000), operating expenses (dollars x 1,000,000), salaries wages and benefits (dollars x 1,000,000), and operating profit margin (by percent), of performing arts companies (NAICS 7111), annual, for five years of data.

This dataset contains the Local Area Unemployment Statistics (LAUS), annual averages from 1990 to 2024.

The Local Area Unemployment Statistics (LAUS) program is a Federal-State cooperative effort in which monthly estimates of total employment and unemployment are prepared for approximately 7,600 areas, including counties, cities and metropolitan statistical areas. These estimates are key indicators of local economic conditions.

The Bureau of Labor Statistics (BLS) of the U.S. Department of Labor is responsible for the concepts, definitions, technical procedures, validation, and publication of the estimates that State workforce agencies prepare under agreement with BLS.

Estimates for counties are produced through a building-block approach known as the "Handbook method." This procedure also uses data from several sources, including the CPS, the CES program, state UI systems, and the Census Bureau's American Community Survey (ACS), to create estimates that are adjusted to the statewide measures of employment and unemployment. Estimates for cities are prepared using disaggregation techniques based on inputs from the ACS, annual population estimates, and current UI data.